Catastrophic transitions or tipping points, where a complex system
shifts suddenly from one state to another, have been implicated in
a wide array of ecological and global climate systems such as lake
ecosystems [1]}, coral reefs [2]},
savannah [3]}, fisheries [4]}, and tropical
forests [5]}. Recent research has begun to identify
statistical patterns commonly associated with these sudden catastrophic
transitions which could be used as an early warning sign to
identify an approaching tipping point, which might provide managers time
to react to and avert an undesirable state shift [6]}, [7]}.
An array of statistical patterns associated with tipping
point phenomena has been suggested for the detection of early warning
signals associated with such sudden transitions. Two of the most commonly
used are a pattern of increasing variance [8]} and a
pattern of increasing autocorrelation [9]}, which have
been tested in both experimental manipulation [10]}, [1]}, [12]}, [13]} and historical
observations [14]}, [15]}, [16]}, [17]}, [18]}, [19]}.
